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Prediction of Typhoon Track and Intensity Using a Generative Adversarial Network With Observational and Meteorological Data
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In
IEEE access : practical research, open solutions 10, Seiten/Artikel-Nr.:48434-48446
2022
Online
DOI: 10.1109/ACCESS.2022.3172301
DOI: 10.18154/RWTH-2022-05400
URL: https://publications.rwth-aachen.de/record/847507/files/847507.pdf
Einrichtungen
- Aachen Institute for Advanced Study in Computational Engineering Science (080003)
- JARA-CSD (Center for Simulation and Data Science) (080031)
- Lehrstuhl für Strömungslehre und Aerodynamisches Institut (415110)
Thematische Einordnung (Klassifikation)
DDC: 621.3
OpenAccess: 
PDF
Dokumenttyp
Journal Article
Format
online
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85129585724
WOS Core Collection: WOS:000793810600001
Interne Identnummern
RWTH-2022-05400
Datensatz-ID: 847507
Beteiligte Länder
Germany, South Korea
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Record created 2022-05-30, last modified 2025-10-14
OpenAccess:
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